Online content services (e.g., collaborative creative services such as Behance®, social media services, etc.) may be customized for certain users to enhance the users' experience. User characteristics for the online content services are modeled and used to match certain online content items (e.g., interesting creative projects) to certain users for recommendation purposes. These modeling techniques thereby increase the user's satisfaction with his or user experience in the online content service. For example, such models derive a real-valued vector for each user that summarizes his or her preferences, habits, and traits in online social platforms. These vectors, which represent users, are generated based on characteristics such as users' ratings of certain online content items, purchases, content consumption, reviews, etc.
However, existing solutions for content customization present disadvantages. For example, models used by existing solutions may rely on user actions that include explicit expressions or indications of a user preference (e.g., ratings, purchases, comments, etc.). But these solutions may fail to leverage other types of data having latent information about user characteristics. For instance, as users perform various actions in content manipulation applications (e.g., image manipulation applications such as Adobe® Photoshop, content creation tools, etc.), log data describing these actions is automatically generated and recorded for collecting application usage statistics and reproducing program errors. The application usage records include noise (e.g., information about user actions without discernible patterns) and are stored in an unstructured manner. The noisy and unstructured nature of application usage records discourages or prevents providers of software applications and online services from using the application usage records to identify user characteristics. Furthermore, if an online content service, such as Behance®, lacks access to usage records generated by a different application, such as Adobe® Photoshop, and the online service is unable to derive any information about a user from those records.
Thus, existing solutions may provide insufficient content customization or other disadvantages for reasons such as (but not limited to) those described above.